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Objective: Optimization of cardiac resynchronization therapy using non-invasive haemodynamic parameters produces reliable optima when performed at high atrial paced heart rates. Here we investigate whether this is a result of increased heart rate or atrial pacing itself. Approach: Forty-three patients with cardiac resynchronization therapy underwent haemodynamic optimization of atrioventricular (AV) delay using non-invasive beat-to-beat systolic blood pressure in three states: rest (atrial-sensing, 66  ±  11 bpm), slow atrial pacing (73  ±  12 bpm), and fast atrial pacing (94  ±  10 bpm). A 20-patient subset underwent a fourth optimization, during exercise (80  ±  11 bpm). Main results: Intraclass correlation coefficient (ICC, quantifying information content mean  ±SE) was 0.20  ±  0.02 for resting sensed optimization, 0.45  ±  0.03 for slow atrial pacing (p   <  0.0001 versus rest-sensed), and 0.52  ±  0.03 for fast atrial pacing (p   =  0.12 versus slow-paced). 78% of the increase in ICC, from sinus rhythm to fast atrial pacing, is achieved by simply atrially pacing just above sinus rate. Atrial pacing increased signal (blood pressure difference between best and worst AV delay) from 6.5  ±  0.6 mmHg at rest to 13.3  ±  1.1 mmHg during slow atrial pacing (p   <  0.0001) and 17.2  ±  1.3 mmHg during fast atrial pacing (p   =  0.003 versus slow atrial pacing). Atrial pacing reduced noise (average SD of systolic blood pressure measurements) from 4.9  ±  0.4 mmHg at rest to 4.1  ±  0.3 mmHg during slow atrial pacing (p   =  0.28). At faster atrial pacing the noise was 4.6  ±  0.3 mmHg (p   =  0.69 versus slow-paced, p   =  0.90 versus rest-sensed). In the exercise subgroup ICC was 0.14  ±  0.02 (p   =  0.97 versus rest-sensed). Significance: Atrial pacing, rather than the increase in heart rate, contributes to ~80% of the observed information content improvement from sinus rhythm to fast atrial pacing. This is predominantly through increase in measured signal. [ABSTRACT FROM AUTHOR]

In this study, we designed and tested a new algorithm, which we call the ‘restricted parabola’, to identify the optimum atrioventricular (AV) delay in patients with biventricular pacemakers. This algorithm automatically restricts the hemodynamic data used for curve fitting to the parabolic zone in order to avoid inadvertently selecting an AV optimum that is too long.We used R, a programming language and software environment for statistical computing, to create an algorithm which applies multiple different cut-offs to partition curve fitting of a dataset into a parabolic and a plateau region and then selects the best cut-off using a least squares method. In 82 patients, AV delay was adjusted and beat-to-beat systolic blood pressure (SBP) was measured non-invasively using our multiple-repetition protocol. The novel algorithm was compared to fitting a parabola across the whole dataset to identify how many patients had a plateau region, and whether a higher hemodynamic response was achieved with one method.In 9/82 patients, the restricted parabola algorithm detected that the pattern was not parabolic at longer AV delays. For these patients, the optimal AV delay predicted by the restricted parabola algorithm increased SBP by 1.36 mmHg above that predicted by the conventional parabolic algorithm (95% confidence interval: 0.65 to 2.07 mmHg, p-value = 0.002).AV optima selected using our novel restricted parabola algorithm give a greater improvement in acute hemodynamics than fitting a parabola across all tested AV delays. Such an algorithm may assist the development of automated methods for biventricular pacemaker optimisation. [ABSTRACT FROM AUTHOR]